Transmitter and method for transmitting soft pilot symbols in a digital communication system

ABSTRACT

A transmitter, channel coder, and method for coding and transmitting a sequence of symbols in a digital communication system utilizing soft pilot symbols. In one embodiment, the transmitter transmits a set of soft pilot symbols with higher reliability than the remaining symbols in the sequence by modulating the soft pilot symbols with a lower order modulation such as BPSK or QPSK while modulating the remaining symbols with a higher order modulation such as 16 QAM or 64 QAM. The transmitter shares the modulation type and location (time/frequency/code) of the soft pilot symbols with a receiver. Unlike traditional fixed pilots, the soft pilots still carry some data. Additionally, the soft pilots are particularly helpful in establishing the amplitude reference essential in demodulating the higher order modulation symbols. In another embodiment, soft pilot symbols are inserted by low-level puncturing of channel encoded bits and replacing the punctured bits with known bit patterns.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.61/073,264 filed Jun. 17, 2008, the disclosure of which is incorporatedherein by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

NOT APPLICABLE

REFERENCE TO SEQUENCE LISTING, A TABLE, OR A COMPUTER PROGRAM LISTINGCOMPACT DISC APPENDIX

NOT APPLICABLE

BACKGROUND

The present invention relates to digital radio communication systems.More particularly, and not by way of limitation, the present inventionis directed to a transmitter and method for transmitting a sequence oftransmitted symbols in a digital communication system utilizing softpilot symbols.

In digital communication systems, the receiver must estimate someparameters in order to correctly demodulate the transmitted data. Thereceiver may also need to estimate a measure of signal quality to feedback to the transmitter. The estimation of parameters/signal qualitygenerally falls into three categories:

(1). Blind estimation. Generally this approach relies on some signal orchannel property/characteristic that is known a priori or learned in aslow manner (for example, second-order statistics). The biggest problemwith blind estimation is performance. Blind estimation generallyunderperforms other approaches by a significant margin. Also, blindestimation algorithms may be more complex.

(2). Pilot-aided. This approach includes known (i.e., pilot) symbols inthe transmitted signal. Pilot symbols can be embedded in the datasequence (for example, the midamble of GSM) or allocated a separateresource such as the pilot code in WCDMA, so long as the pilot symbolsexperience the same effective fading channel as the data. Thepilot-aided approach generally offers the best performance. However,pilot symbols consume resources that might otherwise be devoted totransmitting useful data. Typically there is a tradeoff between havingsufficient pilots for good estimation and maximizing data throughput.

(3). Data-aided. This approach uses demodulated data symbols as “extra”pilot symbols. Generally this approach is used in conjunction witheither blind estimation or the pilot-aided approach. There are twoproblems associated with the data-aided approach. First, blindestimation or pilot-aided estimation (or both) is typically required asa first receiver step. Therefore, data-aided approaches require extrareceiver complexity. Second, data-aided approaches can degrade receiverperformance due to the effect of errors in demodulating data. Indata-aided approaches, the demodulated data symbols are assumed to becorrect and are used as additional pilot symbols. However, if the datasymbols are incorrect, the parameter/signal quality estimationalgorithms can produce incorrect results. The effects of incorrectsymbol decision(s) can persist for more than one estimation interval, sodata-aided approaches may need special mechanisms to avoid the effect oferror propagation.

The data-aided approach has been utilized in a number of existingcommunication systems. For example, in Wideband Code Division MultipleAccess (WCDMA) systems, the control channel on the uplink isdemodulated/decoded, and the symbol decisions are used as effectivepilots. This has also been proposed for the WCDMA control channel on thedownlink. In the Digital Advanced Mobile Phone System (D-AMPS), thechannel is first estimated over a synchronization word and then trackedover data during equalization. In the equalizer, early temporaryunreliable decisions are fed to the tracker, and delayed betterdecisions are fed to the decoder. Also in D-AMPS and GSM, multi-pass(turbo) demodulation/decoding uses decoded/re-encoded symbols aseffective pilots in a second pass.

SUMMARY

The present invention overcomes the disadvantages of the prior art bytransmitting some symbols with higher reliability than others. Theseso-called “soft pilots” are demodulated first and then used as knownsymbols for use in channel estimation and demodulation of higher-ordermodulation symbols (amplitude reference). These soft pilot symbols aremore robust than the surrounding symbols, thereby enabling reliabledecision-directed parameter estimation. Additionally, inserting a“constant envelope” modulation symbol among higher order modulationsymbols is particularly helpful in establishing the amplitude referenceessential in demodulating the higher order modulation symbols.

In one embodiment, the soft pilot symbols are modulated with a simpler,lower order modulation (for example, BPSK or QPSK) compared to the restof the symbol sequence, which is likely a higher order modulation (forexample, 16 Quadrature Amplitude Modulation (16 QAM) or 64 QAM). Byusing these soft pilots, the symbol can still carry some data,contrasted to a fixed pilot symbol, which allows no data throughput forthe symbol. These specified soft symbol locations (time/frequency/code)and the modulation type(s) are shared with the receiver. The receivermay know the information a priori or through signaling.

Soft pilots provide an alternative to explicit data pilots for futurereleases of WCDMA. With soft pilot symbols, explicit pilot symbols arenot necessary. With knowledge of the modulation type and the location ofthe soft pilots in time, frequency, and code, the receiver can maximizeperformance. This allows for better data rates than would otherwise bepossible with explicit pilot symbols.

In another embodiment of the invention, the soft pilot symbols aregenerated by low-level puncturing of channel coded bits. The methodincludes inserting a set of soft pilot symbols by low-level puncturingof channel coded bits and replacing with known bit patterns, modulatingthe sequence, and transmitting the radio signal.

In a specific embodiment related to the High Speed Downlink SharedChannel (HS-DSCH), the soft pilot symbols are generated during thechannel coding chain by low-level puncturing of channel coded bits afterrearranging the modulation constellation and before mapping to aphysical channel. In a specific embodiment related to the EnhancedDedicated Channel (E-DCH), the soft pilot symbols are generated duringthe channel coding chain by low-level puncturing of channel coded bitsafter interleaving on the E-DCH and before mapping to a physicalchannel. With such a mechanism, the use of soft pilots requires nochanges to the specification and implementation of the critical channelcoding and rate matching procedures. This enhances compatibility withlegacy equipment and allows reuse of existing transceiverimplementations.

In another embodiment, the present invention is directed to atransmitter for transmitting a radio signal that includes a sequence oftransmitted symbols. The transmitter includes means for inserting a setof soft pilot symbols by low-level puncturing of channel coded bits andreplacing the punctured bits with known bit patterns; and means formodulating the sequence and transmitting the radio signal.

In another embodiment, the present invention is directed to a channelcoder for channel coding a radio signal for a radio channel. The channelcoder includes means for inserting soft pilot symbols by low-levelpuncturing of channel coded bits; and means for replacing the puncturedchannel coded bits with known bit patterns after channel interleaving.In a specific embodiment, the radio channel is an HS-DSCH. In anotherspecific embodiment, the radio channel is an E-DCH.

According to another embodiment of the invention, the locations of thesoft pilots in terms of time and code (or frequency) are designed toaccommodate time-varying channel responses and to minimize undesirableimpact on code performance and peak-to-average ratios.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

In the following section, the invention will be described with referenceto exemplary embodiments illustrated in the figures, in which:

FIG. 1 is a flow chart illustrating the steps of an exemplary embodimentof the method of the present invention;

FIG. 2 shows the data bit mapping to points in the constellation for 16QAM in one exemplary embodiment of the present invention;

FIG. 3 shows the data bit mapping to points in the constellation for 16QAM in another exemplary embodiment of the present invention;

FIG. 4 (Prior Art) illustrates the existing channel coding chain for theHS-DSCH;

FIG. 5 illustrates the channel coding chain for the HS-DSCH in anexemplary embodiment of the present invention;

FIG. 6 is a flow diagram illustrating an overview of a soft pilotgeneration process in an exemplary embodiment of the present invention;

FIG. 7 is a flow diagram illustrating a soft pilot generation processfor the HS-DSCH in an exemplary embodiment of the present invention;

FIG. 8 is a flow diagram illustrating a soft pilot generation processfor the E-DCH in an exemplary embodiment of the present invention;

FIG. 9 is a functional block diagram of an exemplary embodiment of aninterleaver structure for the E-DCH;

FIG. 10 illustrates a first exemplary embodiment of soft pilot symbollocation;

FIG. 11 illustrates a second exemplary embodiment of soft pilot symbollocation;

FIG. 12 is a functional block diagram of an exemplary embodiment of atwo-pass G-Rake receiver of the present invention; and

FIG. 13 is a flow chart illustrating an exemplary embodiment of aprocessing method performed by the two-pass G-Rake receiver of thepresent invention.

DETAILED DESCRIPTION

For high data rate communications, higher order modulations such as 16QAM and 64 QAM are utilized to increase spectral efficiency. Accordingto a first embodiment of the present invention, the transmitterdesignates certain symbols in the data sequence as so-called “softpilot” symbols by using a specific alternative modulation for thesesymbols. The specific modulation order and the location of these symbols(in terms of time, code, and/or frequency) is known by or signaled tothe receiver. The receiver utilizes the soft pilot symbols to obtain aninitial estimation of signal parameters such as the channel taps and thecorrelation matrix. After a first demodulation, decided symbols may beutilized as effective pilots in a second pass of parameter estimation.By limiting the decided soft pilot symbols to a lower modulation thanthe remaining symbols in the sequence, their decisions are reliableenough to make them useful pilots. The soft pilots are different thantraditional fixed pilots in that some data throughput is carried bythese soft pilot symbols. Thus, replacing traditional fixed pilots withsoft pilots improves data throughput.

FIG. 1 is a flow chart illustrating the steps of an exemplary embodimentof the method of the present invention. At step 11, a radio signal istransmitted with some symbols having higher reliability (for example,with a lower order modulation) than other transmitted symbols. At step12, the radio signal is received and the higher reliability symbols aredemodulated first to form soft pilot symbols. At step 13, the softpilots are utilized as known symbols for channel estimation anddemodulation of the higher order modulation symbols. At step 14, data isextracted from both the soft pilot symbols and the higher ordermodulation symbols.

An exemplary embodiment of the present invention specifies themodulation type and the location (time/frequency/code) of the soft pilotsymbols within the data sequence. According to one embodiment of theinvention, the constellation points of the soft pilots are taken as asubset of the higher order modulation constellation for the datatransmission, such as 16 QAM or 64 QAM. The transmitter may utilize aspecified lower order modulation for the pilot symbols such as BinaryPhase Shift Keying (BPSK) or Quadrature Phase Shift Keying (QPSK). Forthe rest of the symbol sequence, the transmitter may utilize a higherorder modulation (for example, 16 QAM or 64 QAM). These specified softsymbol locations and the modulation type(s) are known by the receiver.The receiver may know the information a priori or through signaling.

Thus the present invention transmits lower order modulation symbolsinserted among higher order modulation symbols, and the receiverperforms associated actions to exploit the lower order modulationsymbols as effective pilots. A symbol can carry a range of number ofbits m: m=0 bit corresponds to a pure pilot; m=1 bit corresponds toBPSK; m=2 bits corresponds to QPSK; and so on, up to the maximum numberM (=6 for 64 QAM). If it is assumed for simplicity that all symbols havethe same energy, then the bit energy and the bit reliability decreasewith m. Thus, the symbols can be used as pilots of various levels ofreliability, and the receiver can perform parameter estimations inmultiple passes.

FIG. 2 shows the data bit mapping to points in the constellation for 16QAM in one exemplary embodiment of the present invention. The fourcorner points of the 16 QAM constellation (shown in the figure asstarred points) are taken as the constellation for the soft pilots. Twofeatures of this embodiment can be readily recognized. First, the softpilot constellation is equivalent to a scaled QPSK constellation. Itthus offers the benefits of constant envelope and higher average power.Second, the soft pilot constellation points can be easily addressedwithin the higher-order constellation by keeping a subset of the bitlabels fixed. In the example shown in FIG. 2, the soft pilotconstellation points are those with the last two bit labels fixed at“11”.

As noted, the use of soft pilot symbols causes the transmitted 16 QAM or64 QAM symbols to have a higher average power. For example, if one inten symbols for one channelization code is a soft pilot symbol, theaverage power is increased by 0.15 dB for 16 QAM and by 0.54 dB for 64QAM. Alternatively, if there are fifteen channelization codes, and onein ten symbols for one of the fifteen channelization codes is a softpilot symbol, the average power is increased by only 0.02 dB for 16 QAMand by 0.04 dB for 64 QAM. In practice, the transmitted power may haveto be reduced by these amounts when utilizing soft pilots. It has beenseen, however, that the net system performance is improved by the use ofsoft pilots.

FIG. 3 shows the data bit mapping to points in the constellation for 16QAM in another exemplary embodiment of the present invention. In thisembodiment, the soft pilot constellation size is enlarged to allowhigher capacity for carrying data. However, the soft pilot constellationprovides a constant quadrature amplitude feature which may be utilizedto derive an amplitude reference. The soft pilot constellation pointsare addressed within the higher-order constellation by fixing the lastbit label to “1.” It is clear to those skilled in the art that analternative soft pilot constellation may be specified by fixing thethird bit label to “1”, providing constant in-phase amplitude.

The introduction of soft pilots reduces the number of channel coded bitsthat can be carried by the transmission signal. The reduction in channelcoded bits can be implemented by two different approaches. In a firstapproach utilizing high-level puncturing, the reduction in channel codedbits is explicitly handled by the entire channel coding chain. Thisapproach may be adopted when designing a new communications system orprotocol. However, backward compatibility is an important factor toconsider when introducing soft pilot symbols into existing systems. Forbackward compatibility, it may be preferred to adopt a second approachutilizing low-level puncturing such that the majority of the channelcoding chain is affected by the new feature. In the following, the HSPAexamples are utilized to illustrate the two approaches in detail.

Soft Pilot Generation in HSPA:

FIG. 4 illustrates the existing channel coding chain for the High SpeedDownlink Shared Channel (HS-DSCH). In a first high-level puncturingapproach for implementing the reduction in channel coded bits, thebehavior of the overall channel coding chain is changed similarly to theone for the HS-DSCH. The impact, however, is not simply a differentnumber of coded bits to be output by the “physical-layer HARQfunctionality”, but rather a significant redesign and redefinition ofseveral inter-connect and intricate physical-layer procedures in“physical-layer HARQ functionality”, “physical channel segmentation”,“HS-DSCH interleaving”, and “Constellation rearrangement”. Suchsignificant redesign of the critical channel coding chain will rendermost of the existing implementation obsolete and will be difficult toco-exist with new and legacy equipment in a network.

FIG. 5 illustrates the channel coding chain for the HS-DSCH in anexemplary embodiment of the present invention. In a second, preferredapproach for implementing the reduction in channel coded bits, the softpilot symbols are preferably generated by low-level puncturing ofchannel coded bits before the “physical channel mapping” stages of thechannel coding chain. The preferred embodiment thus makes the presenceof soft pilot symbols transparent to the “physical-layer HARQfunctionality”, “physical channel segmentation”, “HS-DSCH interleaving”,and “constellation rearrangement” stages.

FIG. 6 is a flow diagram illustrating an overview of a soft pilotgeneration process in an exemplary embodiment of the present invention.In HSDPA, the bit collection procedure in physical-layer HARQfunctionality and the HS-DSCH channel interleaving are designed to mapsystematic turbo-coded bits, if present, to the first bit labels of the16 QAM or 64 QAM as much as possible. The purpose of this design is toensure the important systematic turbo-coded bits are transmitted overthe channel with higher reliability. As shown in FIG. 6, this isaccomplished in the channel interleaver by utilizing pair-by-pair bitmultiplexing and independent rectangular interleavers. When the datamodulation is based on QPSK, only the first rectangular interleaverbranch is active. When the data modulation is based on 16 QAM, the firstand the second rectangular interleaver branches are active. All threebranches are active when the data is carried by 64 QAM. Coupled with theconstellation labeling specified in 3GPP, “Technical Specification GroupRadio Access Network; Spreading and Modulation (FDD),” TS 25.213 v8, thebits in the first branch are transmitted over the channel with highestreliability. The bits in the third branch are transmitted with lowestreliability. Hence, in initial transmissions, the systematic bits arenormally transmitted through the first branch as much as possible. Forinitial transmissions, the HARQ parameters are generally set such thatthe “constellation rearrangement” is effectively by-passed. It should beobvious to those skilled in the art that soft pilot symbols can beinserted right after the channel interleaving. For retransmissions, HARQparameters can be used to instruct the “constellation rearrangement” toeffectively retransmit channel coded bits with different reliability.Soft pilot symbols may be inserted into the signal after the“constellation rearrangement” procedure.

FIG. 7 is a flow diagram illustrating a soft pilot generation processfor the HS-DSCH in an exemplary embodiment of the present invention. Thecoded bit inputs are denoted by r_(p,k) and the outputs are denoted byr′_(p,k). Normally, the input bits are passed to the output withoutmodification: r′_(p,k)=r_(p,k). If a scaled QPSK soft pilot symbol (suchas that shown in FIG. 2) is inserted to replace a 16 QAM data symbol,then r′_(p,k)=r_(p,k), r′_(p,k+1)=r_(p,k+1), r′_(p,k+2)=1, andr′_(p,k+3)=1. If a scaled QPSK soft pilot symbol is inserted to replacea 64 QAM data symbol, then r′_(p,k)=r_(p,k), r′_(p,k+1)=r_(p,k+1),r′_(p,k+2)=1, r′_(p,k+3)=1, r′_(p,k+4)=1, and r′_(p,k+5)=1.

If a soft pilot symbol with constant quadrature amplitude (such as thatshown in FIG. 3) is inserted to replace a 16 QAM data symbol, thenr′_(p,k)=r_(p,k), r′_(p,k+1)=r_(p,k+1), r′_(p,k+2)=r_(p,k+2), andr′_(p,k+3)=1. If a soft pilot symbol with constant quadrature amplitudeis inserted to replace a 64 QAM data symbol, then r′_(p,k)=r_(p,k),r′_(p,k+1)=r_(p,k+1), r′_(p,k+2)=r_(p,k+2), r′_(p,k+3)=1,r′_(p,k+4)=r_(p,k+4), and r′_(p,k+5)=1. If a soft pilot symbol withconstant in-phase amplitude is inserted to replace a 16 QAM data symbol,then r′_(p,k)=r_(p,k), r′_(p,k+1)=r_(p,k+1), r′_(p,k+2)=1, andr′_(p,k+3)=r_(p,k+3). If a soft pilot symbol with constant in-phaseamplitude is inserted to replace a 64 QAM data symbol, thenr′_(p,k)=r_(p,k), r′_(p,k+1)=r_(p,k+1), r′_(p,k+2)=1, r′_(p,k+3),r′_(p,k+4)=1, and r′_(p,k+5)=r_(p,k+5).

Soft Pilot Generation for the Enhanced Dedicated Channel (E-DCH):

FIG. 8 is a flow diagram illustrating a soft pilot generation processfor the E-DCH in an exemplary embodiment of the present invention. Toaccomplish reliability identification similar to that in HS-DSCH, thebit collection procedure in physical-layer HARQ functionality and thechannel interleaving are designed to map systematic turbo-coded bits, ifpresent, to the first bit labels of the 4 PAM as much as possible.According to the preferred embodiment, the soft pilot symbols aregenerated after the E-DCH channel interleaving.

FIG. 9 is a functional block diagram of an exemplary embodiment of aninterleaver structure for the E-DCH. The channel interleaving isfacilitated by two rectangular interleaver branches when the data iscarried by 4 PAM. The coded bit inputs to the “soft pilot generation”are denoted by v_(p,k) and the outputs are denoted by v′_(p,k).Normally, the input bits are passed to the output without modification:v′_(p,k)=v_(p,k). If a scaled BPSK soft pilot symbol is inserted toreplace a 4 PAM data symbol, then v′_(p,k)=v_(p,k), v′_(p,k+1)=1.

According to the preferred embodiment, the soft pilot symbols aregenerated by puncturing channel coded bits at fixed locations (in termsof time and code/frequency). On the receiver side, the soft valuescorresponding to the punctured bits are set to zero. With this, the useof the soft pilot symbols introduces no changes to the corerate-dematching and channel decoder implementation.

Note also that, according to this embodiment, the soft pilot symbols aregenerated by puncturing channel coded bits that are mapped to the leastreliable bit labels. Since the soft values corresponding to theselow-reliability bits are normally very small, setting them to zerointroduces negligible impact to the overall channel coding performance.

Location of Soft Pilot Symbols:

Soft pilot symbols may be imbedded on the same code, on a singleseparate code, on different antennas in Multiple-Input-Multiple-Output(MIMO) systems, and the like. The placement may be coordinated so thatthe soft pilot symbols either coincide or do not coincide on differentcodes and/or antennas.

The soft pilot symbols can be inserted into the signal in severalpractical ways:

1. HSPA—one code assigned to the HSPA user utilizes soft pilot symbolswhile other codes assigned to the same user utilize a higher ordermodulation.

2. HSPA—certain data symbols within each code assigned to the HSPA userare soft pilot symbols while the remaining symbols in the codes areconventional data symbols. For example, symbols 0 through N−1 on code A,N through 2N−1, on code B, and so on may be soft pilot symbols.

3. HSPA—symbols N through 2N are soft pilot symbols on all codesassigned to the HSPA user while the remaining symbols in the codesassigned to the same user are conventional data symbols.

4. Long Term Evolution (LTE)—replace demodulation pilots with soft pilotsymbols for some (or all) of the embedded demodulation pilots.

The following embodiments are designed with further consideration of (a)supporting time-varying channels, (b) minimizing coding performanceimpact, and (c) reducing impact on peak-to-average ratio (PAR).

FIG. 10 illustrates a first exemplary embodiment of soft pilot symbollocation. The soft pilot symbols are spread out in time to provide amore reliable reference for time-varying channels. The exact locationsof the symbols may be specified by periodic patterns. To allow foraveraging for estimation noise reduction, the soft pilot symbols may bepresent in more than one code at the same spread-out locations. Incontrast to concentrating the soft pilot symbols into only one (or veryfew codes), the spread-out pattern across codes minimizes the impact onoverall channel decoding performance.

FIG. 11 illustrates a second exemplary embodiment of soft pilot symbollocation. The embodiment previously illustrated in FIG. 10 is suitableonly if the soft pilot symbols do not contribute to substantial increasein PAR. If the PAR increase is of concern, the embodiment of FIG. 11 canbe adopted. The soft pilot symbol locations between different codes areoffset to reduce PAR increase.

The use of soft pilot symbols provides several benefits. First, the softpilot symbols are more robust than the surrounding symbols, therebyproviding reliable decision-directed parameter estimation. Second, thesoft pilot symbols may still carry some data, contrasted to fixed pilotsymbols, which allow no data throughput for the symbol. Third, by makingthe soft pilot symbols “constant envelope” modulation symbols insertedamong higher order modulation symbols, the soft pilot symbols becomeparticularly helpful in establishing the amplitude reference essentialfor demodulating the higher order modulation symbols.

The use of soft pilot symbols is applicable to any wired or wirelesscommunication system. Soft pilots provide higher data throughput thantraditional pilot-aided schemes, and do not sacrifice performance asmost blind estimation schemes do. The soft pilot approach requires thatthe receiver use a data-aided approach. However, as opposed totraditional data-aided approaches, the present invention specifies themodulation and location (in time/code/frequency) of the soft pilotsymbols so that the receiver will know that there are certainhigh-quality symbols that can be used in a data-aided approach. Receiverestimation algorithms based on such symbols are less error-prone andprovide consistently good parameter and/or signal quality estimates.

An HSPA receiver that can utilize such soft pilots is fully describedbelow in an exemplary embodiment consisting of a data-aided GeneralizedRake (G-Rake) receiver. By way of background, the G-Rake receiverreceives and processes WCDMA signals experiencing interference indispersive channels. This interference is composed of self-interference(intersymbol interference), multiple access interference (interferencedue to non-zero code cross correlation), and other cell (downlink) orother user (uplink) interference. This interference must be suppressedin order to achieve good HSDPA throughput. In addition, the enhancedthroughput requirements set by 3GPP for type 2 (single antenna terminal)and type 3 (dual antenna terminal) receivers cannot be met withoutinterference suppression.

Linear methods for suppressing interference generally fall into thecategories of chip level or symbol level equalization. Symbol levelequalization follows the traditional Rake architecture where thereceived chip-level data is despread at multiple delays, and then themultiple images are combined. Chip level equalization reverses the orderof these operations; the received chip data is first combined using alinear filter and then despread at a single delay. These techniques aregenerally equivalent from a performance perspective.

FIG. 12 is a functional block diagram of a G-Rake receiver 20 which maybe modified to utilize the present invention. The receiver may beimplemented, for example, in a mobile terminal or other wirelesscommunication device. Spread-spectrum signals are transmitted through aradio channel and are received at one or more antennas of the receiver.A radio processor (not shown) generates a series of digitized basebandsignal samples 21 from the received signal and inputs them to the G-RAKEreceiver. In turn, the G-Rake receiver 20 demodulates the receivedsignal samples to produce soft values or bit estimates 22. Theseestimates are provided to one or more additional processing circuits(not shown) for further processing, such as forward-error-correction(FEC) decoding and conversion into speech, text, or graphical images,and the like. Those skilled in the art will recognize that theparticular information type(s) carried by the received signal and theparticular processing steps applied by the receiver 20 are a function ofits intended use and type.

A complete description of a G-Rake receiver suitable for use with thesoft pilot symbols of the present invention is provided in co-owned U.S.Patent Application Publication No. 2005/0201447, the disclosure of whichis incorporated herein by reference in its entirety.

Turning first to symbol level equalization, the G-Rake combining weightsperform the coherent combining as well as interference suppression. Thecombining weights are given by:

w=R _(u) ⁻¹ h,   (1)

where R_(u) is the impairment covariance matrix and h is a vector of netchannel coefficients. It should be noted that the term “impairment”includes both interference and noise while the term “net channelcoefficient” refers to a channel coefficient that includes the effectsof the transmit and receive filters as well as the fading channel.

There are two general methods for implementing a G-Rake receiver. Thesemethods are generally known as nonparametric and parametric. Thenomenclature here focuses on the approach taken to obtain the impairmentcovariance matrix. Nonparametric method(s) are blind, and estimate R_(u)directly from observed data. The parametric method assumes an underlyingmodel, and computes R_(u) from model parameters. Examples of bothmethods are provided below.

There are two ways that one can obtain a nonparametric estimate of theimpairment covariance matrix. The first approach uses the pilot channelto estimate the slot-based quantities:

$\begin{matrix}{{\hat{h} = {\frac{1}{N_{p}}{\sum\limits_{k = 0}^{N_{p} - 1}{{x_{p}(k)}s^{*}}}}}{\hat{R}}_{u,{slot}} = {\frac{1}{N_{p} - 1}{\sum\limits_{k = 0}^{N_{p} - 1}{\left( {{{x_{p}(k)}s^{*}} - \hat{h}} \right)\left( {{{x_{p}(k)}s^{*}} - \hat{h}} \right)^{H}}}}} & (2)\end{matrix}$

Using these quantities, the impairment covariance matrix can be obtainedfrom:

{circumflex over (R)} _(u)(n)=λ{circumflex over (R)}_(u)(n−1)+(1−λ){circumflex over (R)} _(u,slot),   (3)

Another approach for generating a nonparametric estimate of theimpairment covariance matrix involves the use of unoccupied trafficcodes as described in co-owned and co-pending U.S. patent applicationSer. No. 12/135,268 filed Jun. 9, 2008. The despread values for thesecodes contain impairment samples only. These impairment samples can beused to directly estimate R_(u) as follows:

$\begin{matrix}{{\hat{R}}_{u} = {\frac{1}{N_{c}N_{T}}{\sum\limits_{q = 0}^{N_{c} - 1}{\sum\limits_{k = 0}^{N_{T} - 1}{{x_{traffic}^{q}(k)}\left( {x_{traffic}^{q}(k)} \right)^{H}}}}}} & (4)\end{matrix}$

Here, x_(traffic) ^(q)(k) is a despread vector of traffic symbols forthe qth code during the kth symbol interval, N_(T) is the number ofsymbols per code, and N_(c) is the number of codes.

The parametric approach for generating the impairment covariance matrixdepends upon a model for the interference as described in co-owned U.S.Patent Application Publication No. 2005/0201447. This model depends uponthe radio channel(s) between the UE and the modeled base station(s).Assuming a single serving base station and J interfering base stations,the model for the impairment covariance matrix is given by:

$\begin{matrix}{\mspace{79mu} {{R_{u} = {{{E_{c}(0)}{R_{l}^{own}\left( g_{0} \right)}} + {\sum\limits_{j = 1}^{J}{{E_{c}(j)}{R_{l}^{other}\left( g_{j} \right)}}} + {N_{0}R_{n}}}}\mspace{79mu} {{where}\text{:}}}} & (5) \\{{{{R_{l}^{own}\left( {{g_{j};d_{1}},d_{2}} \right)} = {\sum\limits_{\lambda = 0}^{L - 1}{\sum\limits_{n = 0}^{L - 1}{{g_{j}(\lambda)}{g_{j}^{*}(n)}{\sum\limits_{\underset{m \neq 0}{m = {- \infty}}}^{\infty}{{R_{p}\begin{pmatrix}{d_{1} - {mT}_{c} -} \\{\tau_{k}(\lambda)}\end{pmatrix}}{R_{p}^{*}\begin{pmatrix}{d_{2} - {mT}_{c} -} \\{\tau_{k}(n)}\end{pmatrix}}}}}}}}{{R_{l}^{other}\left( {{g_{j};d_{1}},d_{2}} \right)} = {\sum\limits_{\lambda = 0}^{L - 1}{\sum\limits_{n = 0}^{L - 1}{{g_{j}(\lambda)}{g_{j}^{*}(n)}{\sum\limits_{m = {- \infty}}^{\infty}{{R_{p}\begin{pmatrix}{d_{1} - {mT}_{c} -} \\{\tau_{k}(\lambda)}\end{pmatrix}}{R_{p}^{*}\begin{pmatrix}{d_{2} - {mT}_{c} -} \\{\tau_{k}(n)}\end{pmatrix}}}}}}}}}\mspace{79mu} {{R_{n}\left( {d_{1},d_{2}} \right)} = {R_{p}\left( {d_{1} - d_{2}} \right)}}} & (6)\end{matrix}$

Here, E_(c)(j) is the total chip energy for base station j, g_(j) is avector of radio channel (medium) coefficients for the channel betweenthe UE and the jth base station, R_(p)(θ) represents the convolution ofthe transmit and receive pulse shape filters evaluated at θ, τ_(j) is avector of L channel delays corresponding to the channel between the UEand the jth base station, T_(c) is the chip time, and d_(k) is the delayof the kth finger employed by the UE.

Chip equalization is discussed in G. Klutz et al., “Sparse ChipEqualizer for DS-CDMA Downlink Receivers”, IEEE Communication Letters,vol. 9, no. 1, pp. 10-12, 2005. According to Klutz, the received signalat the chip level is given by:

r=Hc+v.   (7)

Here, r is a N+L−1 block of received chips, H is the (N+L−1)×N) sizedToeplitz convolution matrix whose columns are time shifted versions ofthe channel impulse response h with delay spread L (chip or sub-chipspaced version of the net channel coefficients), v represents whiteGaussian noise due to neighboring base stations and thermal noise, and cis the transmitted chip sequence. The chip equalizer filter f thatsuppresses the interference in equation (7) is the solution to:

f=A ⁻¹ b,   (8)

where

-   -   A=E{X^(H)X}    -   b=E{X^(H)C_(p) ^(H)p}    -   X=C_(p) ^(H)R    -   C_(p)=N×S sized pilot scrambling and spreading matrix    -   p=pilot chip sequence

Note that it is assumed that there are S pilot symbols per data blockand that the columns of matrix R are time-shifted versions of the chiplevel received signal r.

Similar to G-Rake, there are several ways to generate the chip equalizerfilter. One may use a parametric approach, a nonparametric approach, anda direct adaptation approach. The parametric and nonparametric formsdiffer (primarily) in how the A matrix is calculated. The nonparametricform uses the received chip data directly to calculate the A matrix via:

$\begin{matrix}{A \approx {\frac{1}{N - L - 1}R^{H}{R.}}} & (9)\end{matrix}$

In contrast, the parametric form works instead with the channel impulseresponse and the powers of the serving base station and the whiteGaussian noise. The entries of the A matrix for the parametric form canbe written as:

$\begin{matrix}{{{A\left( {i,j} \right)} = {{I_{or}{\sum\limits_{n}{{h^{*}(n)}{h\left( {n + \tau_{i} - \tau_{j}} \right)}}}} + {I_{oc}{\delta \left( {i - j} \right)}}}},} & (10)\end{matrix}$

where τ_(k) is the k^(th) chip equalizer tap delay, I_(or) is theserving base station power, and I_(oc) is the white Gaussian noisepower. The direct adaptation approach treats the equalization problem asan adaptive filtering problem. It uses the common pilot signal as aknown reference to train the filter taps using any of the commonadaptive filter algorithms (LMS, RLS, etc.).

The existing parametric and non-parametric equalization approaches havedifferent strengths and weaknesses. The strengths and weaknesses of theG-Rake parametric/nonparametric approaches are discussed below. It isassumed that these strengths/weaknesses hold for chip equalization aswell.

The strength of the parametric approach is that performance (BER, BLER,or throughput) is relatively insensitive to UE speed. The main weaknessof the parametric approach is that it relies on channel informationdeveloped by the path searcher/delay estimator. If this information isincorrect, then the effective color of the impairment will bemis-modeled leading to performance degradation.

The strength of the nonparametric approach is that it is a blindtechnique. There is no specific model for interference, so allinterference is captured by the estimation approach. This blindapproach, however, is also indirectly a weakness. Blind approachestypically need a significant amount of “training” data to perform well.The pilot channel has only 10 symbols per slot, so the pilot-basedapproach to covariance estimation requires significant smoothing(filtering) to work well. Smoothing limits the effectiveness of theapproach to low speed. The unused code approach is highly effective if aset of unused codes can be identified. However, identifying unused codesin the downlink is quite problematic.

It is noted that there is a further weakness inherent in existingequalization techniques. There appears to be an irreducible error floor(i.e., performance ceiling) for practical receiver implementations basedon the existing standard. No such phenomenon occurs for a geniereceiver. In order to increase the peak data rates offered in practice,a practical receiver must more closely mimic the performance of thegenie receiver. It is contemplated that WCDMA release 9 will add morepilot symbols so that nonparametric and/or direct adaptation receiversperform better. The present invention offers an alternative to thisapproach, which reduces the peak throughput only marginally yet stillachieves close to genie receiver performance.

In the two-pass G-Rake receiver of the present invention, the first passcomputes a set of “approximate” or “rough” combining weights. Thesecombining weights are used to coherently combine the symbols from one ormore traffic codes The combined values are resealed to some targetconstellation power and hard symbol decisions are made (i.e., no decoderinvolvement). The hard symbol decisions are then used as demodulationpilots and the impairment covariance matrix is recalculatednonparametrically using these demodulation pilots. From the recalculatedimpairment covariance matrix, a set of second pass combining weights arecomputed. These combining weights are used to coherently combine all thetraffic data. When utilizing soft pilot symbols, the receiver operationis the same except that the first pass combining weights are onlyapplied to the soft pilot symbols.

FIG. 13 is a flow chart illustrating an exemplary embodiment of aprocessing method performed by the two-pass G-Rake receiver of thepresent invention. At step 31, first pass combining weights are created.At step 32 a, despread values for one or more codes are coherentlycombined using the first pass combining weights. Alternatively, theprocess may move to step 32 b where despread values corresponding tosoft pilot symbols are coherently combined to create symbol estimates.At step 33, the symbol estimates are rescaled to some targetconstellation power. At step 34, hard symbol decisions are made on therescaled symbol estimates given the constellation used for transmission.At step 35, the hard symbol decisions are utilized to nonparametricallyestimate the impairment covariance matrix. At step 36, second passcombining weights are computed utilizing the estimated impairmentcovariance matrix. At step 37, all traffic data is combined utilizingthe second pass combining weights.

This process can be realized in different ways depending upon thescenario. For single stream SISO/SIMO/MIMO scenarios, there are twovariants. Similarly for the dual stream MIMO scenario, there are atleast two variants. Each variant is described in an alternativeembodiment below.

First, a single stream SISO/SIMO symbol level embodiment will bedescribed. For the first pass of demodulation, combining weights arecomputed via:

$\begin{matrix}{{w_{first} = {{\hat{R}}_{u,{first}}^{- 1}\hat{h}}},{where}} & (11) \\{{\hat{h} = {\frac{1}{N_{p}}{\sum\limits_{m = 0}^{N_{p} - 1}{{x_{p}\left( {n,m} \right)}s^{*}}}}}{{\hat{R}}_{u,{first}} \approx {\frac{1}{N_{c}K}{\sum\limits_{c = 0}^{N_{c} - 1}{\sum\limits_{k = 0}^{N_{t} - 1}{{x_{t}^{c}\left( {n,k} \right)}\left( {x_{t}^{c}\left( {n,k} \right)} \right)^{H}}}}}}} & (12)\end{matrix}$

In the above equation, x_(p)(n,m) represents a vector of despread commonpilot values corresponding to the m^(th) pilot symbol interval duringthe n^(th) slot, x_(t) ^(c)(n,k) represents a vector of despread trafficvalues corresponding to the k^(th) traffic symbol interval during then^(th) slot for the c^(th) code, N_(p) is the number of common pilotsymbols per slot, N_(c) is the number of traffic codes used forestimation, and N_(t) is the number of data symbols per slot.

It is assumed that a single traffic code is used to create symbolestimates (note: what follows could easily be extended to multipletraffic codes). The first-pass combining weights w_(first) are appliedto traffic code f to create symbol estimates via:

{circumflex over (z)}(k)=w _(first) ^(H) x _(t) ^(f)(n,k).   (13)

These symbol estimates are translated to hard symbol decisions bynormalizing the energy of the symbol estimates to some targetconstellation power (e.g. unity) and then selecting the constellationpoint closest to each symbol estimate. This procedure can be describedmathematically as:

$\begin{matrix}{{\Delta = {\frac{1}{K}{\sum\limits_{k = 0}^{K - 1}{{\hat{z}(k)}}^{2}}}}{{\overset{\sim}{z}(k)} = \frac{\hat{z}(k)}{\sqrt{\Delta}}}{j_{\min} = {{argmin}{{{\overset{\sim}{z}(k)} - {\kappa (j)}}}^{2}{\forall{{\kappa (j)} \in S}}}}{{\hat{s}(k)} = {\kappa \left( j_{\min} \right)}}} & (14)\end{matrix}$

where κ(j) is the value of the j^(th) constellation point taken from theset of constellation points S. The hard decisions are then used toconstruct a more accurate estimate of the impairment covariance matrixvia:

$\begin{matrix}{{{\hat{h}}_{t} = {\frac{1}{N_{t}}{\sum\limits_{k = 0}^{N_{t} - 1}{{x_{t}^{f}\left( {n,k} \right)}{{\hat{s}}^{*}(k)}}}}}{{\hat{R}}_{d} = {\frac{1}{N_{i}}{\sum\limits_{k = 0}^{N_{t} - 1}{{x_{t}^{f}\left( {n,k} \right)}\left( {x_{t}^{f}\left( {n,k} \right)} \right)^{H}}}}}{{\hat{R}}_{u,{second}} = {{\hat{R}}_{d} - {{\hat{h}}_{t}{\hat{h}}_{t}^{H}}}}} & (15)\end{matrix}$

The more accurate estimate of the impairment covariance matrix is thenused to compute the second pass combining weights:

w _(second) ={circumflex over (R)} _(u,second) ⁻¹ ĥ,   (16)

and the second pass combining weights are used to coherently combine allthe despread traffic data.

Another embodiment is the single stream SISO/SIMO chip level/symbollevel embodiment. This embodiment is identical to the symbol levelembodiment except that the matrix {circumflex over (R)}_(u,first) usedto compute first pass combining weights

w _(first) ={circumflex over (R)} _(u,first) ⁻¹ ĥ  (17)

is computed from chip level data. A nonparametric method for realizingthis is described above in the prior art section. Specifically, themethod of equation (9) is adopted, where the columns of matrix R aretime-shifted versions of the chip level received signal r. The setting{circumflex over (R)}_(u,first)=A is made and then the first passcombining weights are calculated. The remainder of the embodiment takesplace at the symbol level and is identical to the single streamSISO/SIMO symbol level embodiment.

Another embodiment is the dual stream MIMO symbol level embodiment. Thisdescription assumes the D-TxAA MIMO transmission scheme standardized inWCDMA release 7 is utilized, although the invention is general enough tocover other 2×2 MIMO schemes. For the first pass of demodulation,combining weights are computed via:

$\begin{matrix}{{w_{{first},1} = {{\hat{R}}_{x}^{- 1}{{\hat{h}}_{eff}\left( b_{1} \right)}}}{w_{{first},2} = {{\hat{R}}_{x}^{- 1}{{{\hat{h}}_{eff}\left( b_{2} \right)}.}}}} & (18) \\{{{\hat{h}}_{1} = {\frac{1}{N_{p}}{\sum\limits_{m = 0}^{N_{p} - 1}{{x_{p}\left( {n,m} \right)}{s_{1}^{*}(m)}}}}}{{\hat{h}}_{2} = {\frac{1}{N_{p}}{\sum\limits_{m = 0}^{N_{p} - 1}{{x_{p}\left( {n,m} \right)}{s_{2}^{*}(m)}}}}}{{h_{eff}\left( b_{1} \right)} = {{b_{11}{\hat{h}}_{1}} + {b_{21}{\hat{h}}_{2}}}}{{{\hat{h}}_{eff}\left( b_{2} \right)} = {{b_{12}{\hat{h}}_{1}} + {b_{22}{\hat{h}}_{2}}}}{{\hat{R}}_{x} \approx {\frac{1}{N_{c}K}{\sum\limits_{c = 0}^{N_{c} - 1}{\sum\limits_{k = 0}^{N_{t} - 1}{{x_{t}^{c}\left( {n,k} \right)}{\left( {x_{t}^{c}\left( {n,k} \right)} \right)^{H}.}}}}}}} & (19)\end{matrix}$

In the above equation, x_(p)(n,m) represents a vector of despread commonpilot values corresponding to the m^(th) pilot symbol interval duringthe n^(th) slot, x_(t) ^(c)(n,k) represents a vector of despread trafficvalues corresponding to the k^(th) traffic symbol interval during then^(th) slot for the c^(th) code, N_(p) is the number of common pilotsymbols per slot, N_(c) is the number of traffic codes used forestimation, N_(t) is the number of data symbols per slot, s₁(m) is them^(th) pilot symbol transmitted from antenna 1, s₂(m) is the m^(th)pilot symbol transmitted from antenna 2, and b₁ and b₂ are the columnsof preceding matrix B used to transmit streams 1 and 2 (i.e. B=[b₁ b₂]).

We assume that a single traffic code is used to create symbol estimates(note: what follows could easily be extended to multiple traffic codes).The first-pass combining weights w_(first,1) and w_(first,2) are appliedto traffic code f to create symbol estimates via:

{circumflex over (z)} ₁(k)=w _(first,1) ^(H) x _(t) ^(f)(n,k)

{circumflex over (z)} ₂(k)=w _(first,2) ^(H) x _(t) ^(f)(n,k).   (20)

These symbol estimates are translated to hard symbol decisions bynormalizing the energy of the symbol estimates to some targetconstellation power and then selecting the constellation point closestto each symbol estimate. This procedure can be described mathematicallyas:

$\begin{matrix}\begin{matrix}{\Delta_{1} = {\frac{1}{K}{\sum\limits_{k = 0}^{K - 1}{{{\hat{z}}_{1}(k)}}^{2}}}} \\{{{\overset{\sim}{z}}_{1}(k)} = \frac{{\hat{z}}_{1}(k)}{\sqrt{\Delta_{1}}}} \\{j_{\min} = {\underset{j}{argmin}{{{{\overset{\sim}{z}}_{1}(k)} - {\kappa (j)}}}^{2}{\forall{{\kappa (j)} \in S}}}} \\{{{\hat{s}}_{1}(k)} = {\kappa \left( j_{\min} \right)}} \\{\Delta_{2} = {\frac{1}{K}{\sum\limits_{k = 0}^{K - 1}{{{\hat{z}}_{2}(k)}}^{2}}}} \\{{{\overset{\sim}{z}}_{2}(k)} = \frac{{\hat{z}}_{2}(k)}{\sqrt{\Delta_{2}}}} \\{j_{\min} = {\underset{j}{argmin}{{{{\overset{\sim}{z}}_{2}(k)} - {\kappa (j)}}}^{2}{\forall{{\kappa (j)} \in S}}}} \\{{{{\hat{s}}_{2}(k)} = {\kappa \left( j_{\min} \right)}},}\end{matrix} & (21)\end{matrix}$

where κ(j) is the value of the j^(th) constellation point taken from theset of constellation points S.

The hard decisions are then used to construct a more accurate estimateof the impairment covariance matrix via:

$\begin{matrix}\begin{matrix}{{\hat{h}}_{t,1} = {\frac{1}{N_{t}}{\sum\limits_{k = 0}^{N_{t} - 1}{{x_{t}^{f}\left( {n,k} \right)}{{\hat{s}}_{1}^{*}(k)}}}}} \\{{\hat{h}}_{t,2} = {\frac{1}{N_{t}}{\sum\limits_{k = 0}^{N_{t} - 1}{{x_{t}^{f}\left( {n,k} \right)}{{\hat{s}}_{2}^{*}(k)}}}}} \\{{\hat{R}}_{d} = {\frac{1}{N_{t}}{\sum\limits_{k = 0}^{N_{t} - 1}{{x_{t}^{f}\left( {n,k} \right)}\left( {x_{t}^{f}\left( {n,k} \right)} \right)^{H}}}}} \\{{\hat{R}}_{x,1} = {{\hat{R}}_{d} - {{\hat{h}}_{t,1}{\hat{h}}_{t,1}^{H}}}} \\{{\hat{R}}_{x,2} = {{\hat{R}}_{d} - {{\hat{h}}_{t,2}{{\hat{h}}_{t,2}^{H}.}}}}\end{matrix} & (22)\end{matrix}$

The more accurate estimate of the impairment covariance matrix is thenused to compute the second pass combining weights

w _(second,1) ={circumflex over (R)} _(x,1) ⁻¹ ĥ _(eff)(b ₁)

w _(second,2) ={circumflex over (R)} _(x,2) ⁻¹ ĥ _(eff)(b ₂),   (23)

and the second pass combining weights are used to coherently combine allthe despread traffic data for both streams.

Note: for the first receiver pass, {circumflex over (R)}_(x) may beobtained using a parametric G-Rake formulation. There is a significantadvantage to this approach if a QAM modulation is employed.

Another embodiment is the dual stream MIMO chip level/symbol levelembodiment. This embodiment is identical to the symbol level embodimentexcept that the matrix {circumflex over (R)}_(x) used to compute firstpass combining weights

w _(first,1) ={circumflex over (R)} _(x) ⁻¹ ĥ _(eff)(b ₁)

w _(first,2) ={circumflex over (R)} _(x) ⁻¹ ĥ _(eff)(b ₂)   (24)

is computed from chip level data. A nonparametric method for realizingthis is described above. Specifically, the method of equation (9) isadopted, where the columns of matrix R are time-shifted versions of thechip level received signal r. The setting {circumflex over (R)}_(x)=A ismade, and then the first pass combining weights are calculated. Theremainder of the embodiment takes place at the symbol level and isidentical to the dual stream MIMO symbol level embodiment.

As will be recognized by those skilled in the art, the innovativeconcepts described in the present application can be modified and variedover a wide range of applications. Accordingly, the scope of patentedsubject matter should not be limited to any of the specific exemplaryteachings discussed above, but is instead defined by the followingclaims.

1. A method of transmitting a radio signal that includes a sequence oftransmitted symbols, said method comprising the steps of: inserting aset of soft pilot symbols into the symbol sequence; modulating thesymbol sequence, wherein the soft pilot symbols are modulated with asimpler, lower order modulation compared to the rest of the symbolsequence; and transmitting the radio signal.
 2. The method as recited inclaim 1, wherein the inserting step includes puncturing channel codedbits with modulation-dependent puncturing positions.
 3. The method asrecited in claim 1, wherein the inserting step includes puncturingchannel coded bits that are mapped to the least reliable bit labels. 4.The method as recited in claim 1, wherein the inserting step includespuncturing channel coded bits that are mapped to the last bit labels ofa modulation symbol.
 5. The method as recited in claim 1, wherein theinserting step includes puncturing channel coded bits that are mapped tothe last two bit labels of a 16 QAM modulation symbol.
 6. The method asrecited in claim 1, wherein the inserting step includes puncturingchannel coded bits that are mapped to the last four bit labels of a 64QAM modulation symbol.
 7. The method as recited in claim 1, wherein thesoft pilot symbols include at least one bit with a known value of
 1. 8.The method as recited in claim 1, wherein as a result of the insertingand modulating steps, the soft pilot symbols are modulated, in effect,with scaled Quadrature Phase Shift Keying (QPSK).
 9. The method asrecited in claim 1, wherein as a result of the inserting and modulatingsteps, the soft pilot symbols are modulated, in effect, with scaledBinary Phase Shift Keying (BPSK).
 10. The method as recited in claim 1,wherein the soft pilot symbols have constant quadrature amplitudes. 11.The method as recited in claim 1, wherein the soft pilot symbols haveconstant in-phase amplitudes.
 12. The method as recited in claim 1,further comprising sending an indication to a receiver indicatinglocations in the sequence for the soft pilot symbols.
 13. The method asrecited in claim 1, further comprising sending an indication to areceiver indicating a modulation type for the soft pilot symbols. 14.The method as recited in claim 1, wherein the inserting step includespuncturing channel coded bits, and the method further comprises sendingan indication to a receiver indicating the punctured bit labelpositions.
 15. The method as recited in claim 1, further comprisingpre-agreeing by the transmitter and a receiver upon the locations ofsoft pilot symbols.
 16. The method as recited in claim 1, furthercomprising pre-agreeing by the transmitter and a receiver upon amodulation type for the soft pilot symbols.
 17. The method as recited inclaim 1, wherein the inserting step includes puncturing channel codedbits, and the method further comprises pre-agreeing by the transmitterand a receiver upon bit label positions for puncturing.
 18. The methodas recited in claim 1, wherein the inserting step comprises high-levelpuncturing of channel coded bits.
 19. The method as recited in claim 1,wherein the inserting step comprises low-level puncturing of channelcoded bits.
 20. A method of channel coding a radio signal for a radiochannel, said method comprising the steps of: channel interleaving theradio signal; inserting soft pilot symbols by low-level puncturing ofchannel coded bits; and replacing the punctured bits with known bitpatterns.
 21. The method as recited in claim 20, wherein the radiochannel is a High Speed Downlink Shared Channel (HS-DSCH).
 22. Themethod as recited in claim 21, wherein the inserting step is performedafter modulation constellation rearrangement.
 23. The method as recitedin claim 21, wherein the inserting step includes puncturing channelcoded bits that are mapped to the last two bit labels of a 16 QAMmodulation symbol.
 24. The method as recited in claim 21, wherein theinserting step includes puncturing channel coded bits that are mapped tothe last four bit labels of a 64 QAM modulation symbol.
 25. The methodas recited in claim 21, wherein as a result of the inserting andreplacing steps, the soft pilot symbols are modulated, in effect, withscaled Quadrature Phase Shift Keying (QPSK).
 26. The method as recitedin claim 21, wherein the soft pilot symbols have constant quadratureamplitudes.
 27. The method as recited in claim 21, wherein the softpilot symbols have constant in-phase amplitudes.
 28. The method asrecited in claim 20, wherein the radio channel is an Enhanced DedicatedChannel (E-DCH).
 29. The method as recited in claim 28, wherein theinserting step includes puncturing channel coded bits that are mapped tothe last bit label of a 4 PAM modulation symbol.
 30. The method asrecited in claim 28, wherein the soft pilot symbols are effectivelymodulated with scaled Binary Phase Shift Keying (BPSK).
 31. The methodas recited in claim 28, wherein the soft pilot symbols have constantamplitudes.
 32. The method as recited in claim 20, wherein the insertingstep includes puncturing channel coded bits with modulation-dependentpuncturing positions.
 33. The method as recited in claim 20, wherein theinserting step includes puncturing channel coded bits that are mapped tothe last bit labels.
 34. The method as recited in claim 20, wherein theknown bit patterns include at least one bit with a value of
 1. 35. Themethod as recited in claim 20, wherein the soft pilot symbols areinserted in at least one code.
 36. The method as recited in claim 20,wherein the soft pilot symbols are not consecutive in time.
 37. Themethod as recited in claim 36, wherein the soft pilot symbols areinserted with a periodic time pattern.
 38. The method as recited inclaim 20, wherein the soft pilot symbols are inserted at the same timelocation in different codes.
 39. The method as recited in claim 20,wherein the soft pilot symbols are inserted at different time locationsin different codes.
 40. The method as recited in claim 20, furthercomprising sending an indication to a receiver indicating locations inthe sequence for the soft pilot symbols, said locations being defined interms of time and code.
 41. The method as recited in claim 20, furthercomprising sending an indication to a receiver indicating a modulationtype for the soft pilot symbols.
 42. The method as recited in claim 20,further comprising sending an indication to a receiver indicating thepunctured bit label positions.
 43. The method as recited in claim 20,further comprising pre-agreeing by a transmitter and a receiver uponlocations of the soft pilot symbols, said locations being defined interms of time and code.
 44. The method as recited in claim 20, furthercomprising pre-agreeing by a transmitter and a receiver upon amodulation type for the soft pilot symbols.
 45. The method as recited inclaim 20, further comprising pre-agreeing by a transmitter and areceiver upon bit label positions for puncturing.
 46. A transmitter fortransmitting a radio signal that includes a sequence of transmittedsymbols, said transmitter comprising: means for inserting a set of softpilot symbols into the symbol sequence; means for modulating the symbolsequence, wherein the soft pilot symbols are modulated with a simpler,lower order modulation compared to the rest of the symbol sequence; andmeans for transmitting the radio signal.
 47. A channel coder for channelcoding a radio signal for a radio channel, said channel codercomprising: means for channel interleaving the radio signal; means forinserting soft pilot symbols by low-level puncturing of channel codedbits; and means for replacing the punctured channel coded bits withknown bit patterns.
 48. The channel coder as recited in claim 47,wherein the radio channel is a High Speed Downlink Shared Channel(HS-DSCH).
 49. The channel coder as recited in claim 47, wherein theradio channel is an Enhanced Dedicated Channel (E-DCH).